System and method for performing progressive beamforming

ABSTRACT

A progressive beamformer in an imaging system includes a number of stages. A first stage delays and combines a number of received data streams to align the streams to a point of interest on a first beamline. The first stage feeds a number of subsequent stages that operate to buffer and re-delay at least a portion of the data streams received from a previous stage in order to align the data streams to a point of interest on a new beamline. In one embodiment, each stage operates to reduce the number of data streams that are passed to a subsequent stage without suffering from grating lobes. A beam reclamation process includes a number of stages that receive data streams from end elements in order to produce reclaimed beams that are added to beamline produced in a mainline beamforming process in order to produce output beamlines.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/831,436 filed Mar. 14, 2013, and which is incorporated herein in itsentirety.

TECHNICAL FIELD

The disclosed technology relates generally to beamforming techniques andin particular to systems for beamforming in ultrasound imaging systems.

BACKGROUND

In ultrasound imaging systems, images of a tissue region are created bytransmitting one or more acoustic pulses into the body from atransducer. Reflected echo signals that are created in response to thepulses are detected by the same or a different transducer. The echosignals cause the transducer elements to produce electronic signals thatare analyzed by the ultrasound system in order to create a map of somecharacteristic of the echo signals such as their amplitude, power, phaseor frequency shift etc. The map therefore can be displayed to a user asan image of the tissue.

Most imaging ultrasound transducers have a number of individualpiezoelectric transducer elements that are typically arranged in alinear, curved, concentric or two-dimensional array. In some cases, thearray may be one element wide such as 128×1 elements. In other cases,higher dimensional arrays such as 128×2, 128×4 . . . 128×128 elementsare used.

In order to accurately determine a characteristic of an echo signal at aparticular location or point of interest (“POI”) in the body, thesignals from multiple transducer elements are analyzed. However, theacoustic echo signals generated at any given POI reach each of thetransducer elements at slightly different times. Therefore, theultrasound system performs a task of beamforming that aligns thereceived echo signals from the various transducer elements so that theecho signals originating from the same POI can be analyzed. Beamformingtypically involves storing the signals from each transducer element byat least an amount of time equal to the time it takes for an acousticsignal to reach the transducer elements that are the farthest from aPOI. Some systems store signals from an entire region of interest. Thestored signals from a number of the transducer elements are thendelayed, aligned, weighted and combined to determine a characteristic ofan echo signal at a particular POI.

Beamforming is generally the most computationally intensive task that isperformed by programmable or special purpose processors (e.g. DSPs)within an imaging system. The beamforming process therefore contributessignificantly to the processing time required to produce images oftissue in the body. The overhead increases the time required to produceimages as well as the cost and complexity of the processing componentsof the imaging system and the electrical power required to run thosecomponents.

SUMMARY

A progressive beamforming system includes a series of stages including afirst stage and a number of subsequent stages. In the first stage, adata stream is received from transducer elements that represent signalsfrom a field of view. The data stream samples are delayed to align thedata stream to a point of interest on a first beamline. A weightedcombination of the data stream samples is generated to reduce a numberof elements in the data stream. In a subsequent processing stage, thedata streams from the previous stage are received are re-delayed toalign the data stream to a second point of interest on a secondbeamline. Weighted combinations of the re-delayed elements are thencombined to further reduce the number of elements.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a conventional method of beamforming in an ultrasoundimaging system;

FIG. 2 illustrates a method of progressive beamforming (“PBF”) inaccordance with an embodiment of the disclosed technology;

FIG. 3 is a block diagram showing the functional components of aprogressive beamformer with digital stacking (“DS”) in accordance withan embodiment of the disclosed technology;

FIGS. 4A and 4B illustrate how a grating lobe can be created based onthe spacing of transducer elements and the frequency of receivedsignals;

FIG. 5 illustrates a narrow band beam pattern with no significantgrating lobes.

FIG. 6 illustrates a narrow band beam pattern with significant gratinglobes;

FIG. 7 illustrates a broadband beam pattern with significant gratinglobes;

FIG. 8 illustrates the response of a PBF imaging system without DS(grating lobe cancellation (“GLC”)) and with significant grating lobes;

FIG. 9 illustrates the response of a PBF imaging system with DS (gratinglobe cancellation) after each stage in the progressive beamformer inaccordance with one embodiment of the disclosed technology;

FIG. 10 illustrates the response using a conventional beamformer;

FIG. 11 illustrates an assembly of super elements at a first stage of aprogressive beamformer with DS in accordance with one embodiment of thedisclosed technology;

FIG. 12 illustrates an assembly of super elements at a second stage of aprogressive beamformer with DS in accordance with one embodiment of thedisclosed technology;

FIG. 13 illustrates an assembly of super elements at a third stage of aprogressive beamformer with DS in accordance with one embodiment of thedisclosed technology;

FIG. 14 illustrates an assembly of super elements at a fourth stage of aprogressive beamformer with DS in accordance with one embodiment of thedisclosed technology.

FIG. 15 illustrates an assembly of super elements at a reclamation stageof a progressive beamformer with DS in accordance with one embodiment ofthe disclosed technology;

FIG. 16 illustrates a beam reclamation process in accordance with anembodiment of the disclosed technology; and

FIG. 17 illustrates how reclaimed beams are added to mainline beams inaccordance with an embodiment of the disclosed technology.

DETAILED DESCRIPTION

The technology disclosed herein relates to improvements in beamforming.Although the technology is described with respect to its use withultrasound imaging systems, it will be appreciated that the technologycan also be used in other imaging systems such as sonar, radar,non-destructive test, MRI, acoustics, astronomy or in other environmentswhere mechanical, electrical or electromagnetic wave signals aretransmitted into a region of interest and information is gathered inresponse to the signals. For example, photo-acoustic imaging is atechnique where laser light is transmitted into a body or other objectand acoustic signals are created due to the differential heating of thetissue/object. The differential heating produces acoustic signals thatcan be detected and beamformed in accordance with the disclosedtechnology.

As discussed above, conventional beamforming is a process wherebysamples from a number of transducer elements are stored and aligned sothat samples reflecting echoes that originate from the same location orPOI in a body can be combined in order to produce an image of a tissuecharacteristic at that particular location.

FIG. 1 illustrates a conventional beamforming system whereby acousticpulses are delivered into a tissue sample from an ultrasound transducer100. In the example shown, the transducer 100 has a linear array of 127transducer elements E₀-E₁₂₆. However, it will be appreciated that othertransducer sizes or shapes such as convex, concentric or two-dimensionalarrays could be used.

Many ultrasound systems create an image of a tissue region usingmultiple field of views (FOVs) or slices of the region. Depending on theshape of the transducer, the FOV may be rectangular or arcuate in shape.The beamforming is performed by storing and combining data streams toproduce a value for an echo signal characteristic at a number ofpositions on individual beamlines within each FOV. Echo signals from allor a subset of the transducer elements are analyzed to determine theecho characteristic (amplitude, power, phase-shift etc.) at a number oflocations along each beamline. For example, a beamline A includes anumber of POIs A1, A2, A3, while a beamline B includes a number of POIsB1, B2, and B3. In the example shown, the FOV includes 33 beamlines;however only two beamlines, beamline A and beamline B, are identified.

In the example shown, an echo signal originating from the POI A1 expandsoutward as a spherical wave WA. The relative location of the transducerelements and the POI A1 means that wave WA encounters the closesttransducer elements such as element E₄₈ before the wave encounterstransducer element E₁₂₆ at the end of the array. To align the signalsfor the POI A1, a stream of samples from the transducer elements arestored for at least a period equal to the difference in time betweenwhen the echo signals reach the closest elements (e.g., element E₄₈ forthe example wave WA described above) and when the same wave reaches thefarthest transducer elements in the transducer (e.g., element E₁₂₆ forthe example wave WA described above). In addition, a digital filter istypically used to interpolate between the digital samples during thebeamforming process. The interpolated samples from each of thetransducer elements are aligned, weighted and combined to produce avalue for the echo signal at the POI A1. The process is repeated for thenext POI A2 on the beamline until data for the entire beamline iscomputed.

Most modern ultrasound systems perform parallel beamforming where datafor a number of beamlines in a FOV are simultaneously calculated. In theexample shown in FIG. 1, data for the beamlines A and B aresimultaneously calculated. To calculate the data for the beamline B,digital samples from each of the transducer elements are read frommemory, aligned and summed in the same manner as beamline A. Because thedelays associated with a spherical wave A that originates from POI A1 onbeamline A and a spherical wave B that originates from POI B on beamlineB are nearly identical, virtually the same calculations aresimultaneously performed to compute the data for each beamline. The datafor sets of beamlines within a FOV are typically stored until all thedata for all the beamlines in each of the FOVs have been computed, atwhich time an image can be created and displayed.

The technology disclosed herein decreases the number of nearlyrepetitive calculations that are performed when calculating data for anumber of beamlines in a FOV by taking advantage of the closely relateddelays used to create data for a beamline. To reduce the number of delayand summing operations required to perform simultaneous beamforming, thedisclosed technology re-delays and re-combines samples from transducerelements in various stages order to calculate the data for anotherbeamline within a FOV.

As illustrated in FIG. 2, one embodiment of the disclosed technologyalso employs the linear ultrasound transducer 100 that includes 127transducer elements E₀-E₁₂₆. Acoustic echo signals that are received bythe transducer elements create corresponding electrical signals, whichare digitized by an analog-to-digital converter for temporary bufferingin a digital memory and analysis by a processor (not shown). FIG. 2illustrates a FOV 120 that includes 33 beamlines including a centralbeamline C, located in the center of the FOV 120 and that includes POIsC0, C1, C2, C3 etc. Similarly, beamline D at an edge of the FOV 120includes POIs D0, D1, D2, D3 etc. Echo signals originating from the POIC0 on beamline C expand out as a spherical wavefront WC. As will beappreciated, the wavefront WC reaches the farthest transducer elements,such as element E₁₂₆, after the wavefront reaches the closer transducerelements such as element E₄₈. To align the signals for calculating thedata for the POI's on beamline C, the digital samples are delayed in amemory having at least a depth or size sufficient to store samples for atime that is represented by the bracket 140 to support alignment fromall contributing elements.

In contrast to repeating nearly the same delay calculations to determinedata for points on each beamline, the disclosed technology operates tobuffer and re-delay a portion of the signals that were used to calculatethe data for the points on first beamline in order to calculate the datafor points on additional beamlines. In the example shown, samplesrepresenting the echo signals that originate from POIs D0, D1, D2, D3 onbeamline D are calculated by re-delaying a portion of the digitalsignals stored to calculate the data for the POIs on beamline C. Thewavefronts of waves WD originating from POIs D0-D3 arrive at thetransducer elements at times that are only slightly different than thewavefronts of waves WC originating from POIs C0-C3. Therefore the datafor the POIs on beamline D can be calculated by buffering andre-aligning digitized echo signals that are close in time to the samplesthat were used in calculating the data for points on beamline C. In theexample shown, the wavefront WD (shown in dashed lines) reaches theleft-most transducer element E0 before the wavefront WC originating froma point on beamline C. Therefore, data from the elements is buffered ina memory buffer having a depth at least as long as this time differenceand the samples that arrive before the wavefront We can be used tocompute the data for beamline D. On the other side of the transducer,the wavefront WD arrives at transducer element E₁₂₆ after the wavefrontWC. Therefore data is buffered in a memory having a depth 152, which isat least at long as this time difference. Samples arriving after thewavefront WC has passed are used to produce the data for POIs on thebeamline D.

As will be appreciated, the closer the beamlines are in the FOV, theless time difference occurs between the time at which the wavefrontsarrive at the various transducer elements and correspondingly lessmemory is required to buffer the digitized echo signals in order toalign the data for the POIs on another beamline. Because the timedifference is short, significantly less buffer memory is needed thanthat needed to align the wave fronts for points originating on beamlineC.

As will be explained in further detail below, one embodiment of thedisclosed technology operates to calculate the data for a number ofbeamlines in stages. For the various stages, a portion of the datastreams used to calculate data for a beamline in a previous stage arebuffered and re-delayed to calculate the data for a new beamline. In oneembodiment, the number of transducer elements is reduced after eachstage by combining the data streams from selected transducer elements.The result is a beamforming system that simultaneously increases thenumber of beamlines at each stage and reduces the number of data streamsfrom transducer elements to be analyzed.

FIG. 3 illustrates a functional block diagram of a beamforming system inaccordance with one embodiment of the disclosed technology. In theembodiment shown, a portion of the data streams from the elements of thetransducer are first buffered and delayed to calculate data for a POI ona center beamline. A portion of the data streams used to compute thePOI's in the first computed beamline are then buffered and re-delayed inorder to produce data for additional beamlines. This process repeats insubsequent stages by buffering the data streams from a previous stageand re-delaying the buffered streams in order to calculate data foradditional beamlines that lie between the previously calculatedbeamlines.

In one embodiment, the number of data streams analyzed in each stage ofthe beamformer is reduced by combining data from adjacent streams. Forexample, the data streams from nine transducer elements E₀-E₈ can becombined using a weighted sum of adjacent streams such as (E₀+2×E₁+E₂;E₂+2×E₃+E₄; E₄+2×E₅+E₆; E₆+2×E₇+E₈.) in order to reduce the nine streamsto four. By combining streams, the transducer elements are effectivelyincreased in size to create “super elements” or (“SE”). The next stagein the progressive beamformer operates to buffer and re-delay the datastreams from these combined streams to produce data for additionalbeamlines and reduce the number of data streams from transducer elementsthat are again effectively doubled in size. The streams from thesecombined streams are then buffered and re-delayed in a subsequent stageto create the data for additional beamlines and so on such that eachstage fills in data for points on beamlines that lie between thepreviously calculated beamlines until the data for all the desiredbeamlines in the FOV are calculated.

The progressive beamforming uses significantly fewer delay calculationsthan the prior art methods. The table set forth below, shows the savingsin the number of delay blocks used to produce 33 beam lines.

Number Output PBF Cumulative Prior Art of Output Super Output TotalTotal Output Multi-Line Delayed Super Element Additional Output DelayDelay Delay Elements Elements Size Beams Beams Blocks Blocks Blocks 12763 2 1 1 127 127 127 63 31 4 2 3 126 253 381 31 15 8 2 5 62 315 635 15 716 4 9 60 375 1143 7 3 32 8 17 56 431 2159 3 1 64 16 33 48 479 4191

In the embodiment shown in FIG. 3, an ultrasound transducer 300 includesa number (e.g. 127) of active transducer elements. Each of thetransducer elements produces a corresponding stream of digital data inresponse to received echo signals. In a first stage, the data streamsfrom each of the 127 transducer elements are stored in a buffer 310. Inone embodiment, the buffer 310 has a depth (i.e. size) sufficient tostore the samples produced during a time period that is equal to thetime difference between when the wavefronts from a POI arrive at theclosest transducer elements in an array and the time at which thewavefronts reach the farthest transducer elements in the array. Once thewavefronts from the POI have been received by each of the transducerelements, the buffered data are aligned to produce the data for a POI ona first beamline. In the embodiment shown, the first beamline is in thecenter of the field of view. However this is not required.

To calculate the data for the POIs on the first beamline, the streamspass through a buffer and are delayed at 310 in order to focus thebuffered data at a point on a first beamline. The buffer may include amulti-tap filter used to interpolate data between sample points. Thebuffer and filter can be implemented as a FIFO memory. In oneembodiment, the data streams from neighboring transducer elements areweighted and combined by a programmed processor, DSP or ASIC or otherelectronic circuit at 320 to reduce the number of data streams by afactor of two as indicated above.

In the second stage of the progressive beamformer, a portion of theresulting 63 data streams are then buffered at 330, 332, 334. To focusthe data on the two outer-most beamlines, the data buffered at 330 and334 are re-delayed. The data buffered at 332 is already focused at apoint along the center beamline and the buffer is only used so that thedata from the three beamlines is produced simultaneously. The 63 datastreams used to produce the data for POIs on the three beamlines instage 2 are then weighed and combined at 350, 352 and 356 to reduce thenumber of data streams by a factor of two and to increase the effectiveelement size. At the end of stage 2, there are data for 3 beams from 31elements of effective size 4.

In stage three, a portion of the 31 data streams are then buffered at360, 362, 364, 366 and 368. The data for the center and outer-mostbeamlines are already focused and therefore no re-delays are needed forthese buffered data streams. These data streams are weighted andcombined to reduce the number of data streams and to increase theeffective element size via combining blocks 370, 374 and 378. The databuffered at 362 and 366 is re-delayed to focus the data streams onpoints on the new beamlines that are positioned between the centerbeamline and the two outer-most beamlines and then weighted and combinedto reduce the number of data streams and to increase the effectiveelement size at blocks 376, 372. After stage 3 in the progressivebeamformer, data are computed for points on 4 new beamlines from 15 datastreams each with an effective element size of 8.

Processing continues in this manner by buffering a portion of the datastreams from a previous stage and re-delaying the buffered data streamsas necessary to focus the buffered data on a new beamline. In addition,each stage reduces the number of data streams and increases theeffective element size.

In the exemplary embodiment shown, stage 4 of the progressive beamformerproduces data for points on 9 beamlines represented by 7 data streamseach having an effective element size of 16. In stage five, data arecomputed for points on 17 beamlines represented by 3 data streams eachhaving an effective element size of 32. Processing continues in thismanner until there are 33 beamlines (or however many are required)represented by a single data stream (or however many are required) withan effective element size of 64 (or however many are required).

In one embodiment, once the original data streams fill the buffer at310, then for each additional set of samples received in the 128 datastreams produced from the transducer, data for the next depth POI in all33 beamlines are output in parallel at the end of the progressivebeamformer stages.

As will be explained in further detail below, the contribution from theend data streams of the transducer are diminished as a result of the wayin which the data streams are combined. Therefore the data for theoutermost data streams each stage is reclaimed and added back into thefinal result of the progressive beamforming process. For purposes ofillustration the process shown in FIG. 3 can be referred to as the“primary” or “mainline” beamforming process and adding back the datafrom the outermost data streams is called the “aperture reclamation”process.

Beamlines for a new FOV can then be created by repeating the above stepsuntil the echo signals for an entire tissue area or region of interesthave been processed and an image can be produced from the beamlines in aconventional manner.

As will be appreciated by those skilled in the art, beam patternsconsist of a main lobe, a region of side lobes, and possibly gratinglobes. The main lobe is in essence the beam. Practically, it is the mostsensitive part of the beam pattern as it is the point to which all thedelays are referenced. Its width is inversely related to the size of thesensing array. Side lobes are unwanted sensitivity to sources at otherpoints in space. Side lobes are controlled by applying various weightingfunctions to the elements before summation in a procedure referred to as“apodization.” Typically, functions that decrease gracefully toward zeroprovide lower side lobe levels usually at the expense of the main lobewidth. Grating lobes are a spatial alias of the main lobe and posesignificant problems for any beamformer. They only occur when the fieldis too sparsely sampled. That is, at any particular frequency, if theelement centers are spaced far enough apart, the phasing across thearray from a source in one location is indistinguishable from a sourcein another location. The weighting function applied to the aperture tocontrol side lobes cannot reduce the grating lobe, but rather, widens itas it does also the main lobe.

For a plane wave impinging upon a linear array, the grating lobeoccurrence is well understood. As can be seen in FIG. 4A, when acontinuous plane wave (depicted by the constant phase lines) is broadside to a linear array, the signal at each of the elements (boxes) isthe same. When the plane wave comes from a different direction, □, thenthere is a point at which the phases appear from the element signalperspective to be at the same phase albeit from different cycles asshown in FIG. 4B. This is the grating lobe caused where the incidentenergy goes through some integer multiple of 2□ between elements. Whenelements are spaced less than kd·sin(θs)=+/−2πn, where k=2π/□□□□d is thespacing between element centers and θs is the angle with respect to theperpendicular of the transducer array, it is apparent that grating lobesare impossible since there is no solution for integer n as shown in FIG.5. When elements are delayed to form a beam along the angle θp then thegrating lobe relationship is kd·(sin θs−sin θp)=+/−2πn□□□□Many gratinglobes can occur for a spacing that is sparser.

For completeness, it should be noted that whereas the main lobe positionis constant over frequency, the grating lobe moves as its position isdependent on frequency. Thus, broad band grating lobes do not appear assevere as narrow band ones. The grating lobe strength is usually lessthan the main beam as it is modulated by the element pattern.

The progressive beamforming technique described herein is filled withdelays applied to elements or super elements which have spacing muchgreater than the half wavelength as noted above. Thus, grating lobes areto be expected. Whereas random beamforming errors give rise to randomside lobe variations, progressive beamforming delay errors are periodicwhich gives rise to structure in the beam pattern. FIG. 6 illustrates anexample of a narrow band beam pattern with grating lobes.

FIG. 7 shows a broad band grating lobe. Note that the broad bandspectrum smears the grating lobe position.

By a very simple operation called digital stacking (“DS”) at eachprogressive beamforming stage, these unwanted grating lobes may besubstantially reduced or eliminated assuming that the original elementspacing (pitch) is smaller than a half wavelength. In one embodiment,this is accomplished by summing three adjacent elements with a 1-2-1proportioned weighting instead of simply summing pairs of elements witha 1-1 proportioned weighting. This can be seen by the followingderivation.

Grating lobes occur in the far field whenever the angle of the planewavefront and beamforming delays meet the relationship of

kD(sin θ_(s)−sin θ_(p))=±2πn

where θ_(s) is the direction of the acoustic source, θ_(p) is thepointing direction of the beam, D is the spacing between the arrayelements, and k is the wave number 2π/λ. Expressing the spacing inwavelengths gives

${\frac{D}{\lambda}\left( {{\sin \; \theta_{s}} - \sin_{p}} \right)} = {\pm n}$

When D<λ/2, there is no chance of grating lobes. D can be larger so longas source and pointing directions are not severe. When D is largecompared to a wave length, then many grating lobes can exist.

Consider when three adjacent elements are summed with a 1-2-1 weightingto form a larger element. Assume two adjacent elements are summed andwithout loss of generality reference the phase to the first one:

e ₁₂=1+e ^(jkd(sin θ) ^(s) ^(-sin θ) ^(p) ⁾

where θ_(s) is the direction of the acoustic source, θ_(p) is thedirection of the beam, d is the spacing between elements, and k is thewave number 2π/λ. The sum of the second and third elements is:

e ₂₃ =e ^(jkd(sin θ) ^(s) ^(-sin θ) ^(p) ⁾ +e ^(j2kd(sin θ) ^(s) ^(-θ)^(p) ⁾

Summing these two pairs together gives

e ₁₂ +e ₂₃+1+2e ^(jkd(sin θ) ^(s) ^(-sin θ) ^(p) ⁾ +e ^(j2kd(sin θ) ^(s)^(-sin θ) ^(p) ⁾

which can be reduced to the following form:

${e_{12} + e_{23}} = {2\; {^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}\left\lbrack {1 + \frac{\; {^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + \; ^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}}{2}} \right\rbrack}}$e₁₂ + e₂₃ = 2 ^(j kd(sin  θ_(s) − sin  θ_(p)))[1 + cos (kd(sin  θ_(s) − sin  θ_(p)))]${e_{12} + e_{23}} = {4\; ^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}{\cos^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}$

Note that this equation is a zero when the cosine argument is zero,namely when

${{\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {{\pm m}\frac{\pi}{2}}};{m\mspace{14mu} {odd}}$

or expressing element spacing in terms of wave lengths,

${{\frac{2\; d}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {odd}}$

As can be easily seen, when D of the grating lobe equation is 2d of thezeros of the 1-2-1 weighting equation, the 1-2-1 weighting provides twozeros at exactly the location the grating lobe occurs when n and m areboth unity. That is, when adjacent elements spaced d center-to-centerare summed in a 1-2-1 fashion to form about half the number of elementsspaced 2d center-to-center, the grating lobes created by the summing anddecimation process are cancelled. And this is true at every frequencysimultaneously.

It should also be noted that when the original pitch precludes thepresence of grating lobes, then summing these elements in a 1-2-1fashion and decimating by two will result in elements that are twice aslarge, element centers spaced twice as far apart, and have no gratinglobes. This summation and decimation can continue in stages to produceincreasingly fewer and larger elements that have no grating lobes at allfrequencies.

Because grating lobes occur at every integer n and zeros only occur atodd integer m, it is easiest to create and remove just the first gratinglobe at a time in stages. If two grating lobes are created largerdecimations such as by three instead of two, two grating lobes may becreated. For example, if D<1.5λ, then

${\frac{3}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} < {\pm n}$

which means n could be either 1 or 2 depending on the differencesbetween sine functions of the source and steering directions being ±2/3or ±4/3. In this case, the weighting function would have to produce twosets of zeros, one set for each of the grating lobes. That is, m wouldhave to take on two odd values such as 1 and 3 for the same value of dor two values of d for one value of m. For example,

${\frac{2\; d}{\lambda}\left( \frac{2}{3} \right)} = {\pm m_{1}}$${\frac{2\; d}{\lambda}\left( \frac{4}{3} \right)} = {\pm m_{2}}$

where m₁ and m₂ must be odd. Since the left hand sides are related by afactor of two, this cannot be accomplished. Clearly only odd gratinglobes can be removed by a single value of d. For example, if D=1.5λ,then the first and third (at +/−90 degrees) grating lobes would becancelled but not the second.

If, however, a second element spacing could be accommodated becausedifferent elements can be created by different groupings of subelements, then with one value of m equating the two equations

${\frac{2\; d_{1}}{\lambda}\left( \frac{2}{3} \right)} = {\pm m}$${\frac{2\; d_{2}}{\lambda}\left( \frac{4}{3} \right)} = {\pm m}$gives d₁ = 2 d₂

For m=1, d₁ would need to be ¾λ, and d₂ would need to be ⅜λ indicatingthe need for even smaller sub element spacing to create a d₂ pitchrelated to the higher valued grating lobe. Clearly, other values of mcould be used with other element pitches.

As D increases in wave lengths, n takes on numerous contiguous integervalues according to

${\frac{D}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm n}$

that is n=1, 2, 3, 4, When D=2d, only the odd numbered grating lobes(n=1, 3, 5, . . . ) are mitigated leaving all the even numbered onesunaffected according to

${{\frac{2\; d_{1}}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {odd}}$

However, if another array is created with d2=½d1, then the grating lobesof n=2, 6, 10, 14, . . . can be mitigated by

${{\frac{2d_{2}}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {odd}}$

In this way, grating lobes of n=1, 2, 3 can be mitigated allowing D tobe as large as 3/2λ. Creating another array of elements spaced d₃=½d₂=¼d₁, then the grating lobes of n=4, 12, 20, 28, . . . can bemitigated by

${{\frac{2d_{3}}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {odd}}$

In this way, grating lobes of n=1, 2, 3, 4, 5, 6, 7 can be mitigatedallowing D to be as large as 7/2λ.

Continuing on in the same fashion, d4=½ d3=¼ d2=⅛d1 accommodates gratinglobe number from 1 to 15 and D to be as large as 15/2λ.

In general, larger groupings of sub elements forming larger superelements requires a larger number of co-located arrays of smallerpitches. For N−1 contiguous grating lobes to be suppressed, log 2Narrays are needed with pitches that correspond to λ/(2*log₂ N). In orderto take advantage of these arrays, one would have to combine them in away that has the effect of multiple zeros of the cos 2 function of the1-2-1 weighting combine as factors.

For example, one would desire a weighting operation for D=λ that wouldresult in cosine factors that mitigate the two grating lobescorresponding to n=1 and 2. That is, a pair of zeros are desiredcorresponding to d1 and d2=½ d1. Thus, it is desired to have

$\mspace{79mu} {{\cos^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}{\cos^{2}\left( {\frac{kd}{4}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}$$\mspace{79mu} {\frac{1 + {\cos \left( {{kd}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}{2}*\frac{1 + {\cos \left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}{2}}$${\frac{1}{4}\left\lbrack {1 + \frac{^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + ^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}{2}} \right\rbrack}{\quad{\left\lbrack {1 + \frac{^{j\frac{kd}{2}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}} + ^{{- j}\frac{kd}{2}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}{2}} \right\rbrack \frac{^{{- j}\frac{3\; {kd}}{2}\sin \; \alpha}1}{16}\left\{ {1 + {2^{j\frac{kd}{2}\alpha}} + {3^{j\; {dk}\; \alpha}} + {4^{j\frac{3{kd}}{2}\alpha}} + {3^{{j2}\; {kd}\; \alpha}} + {2^{j\frac{5{kd}}{2}\alpha}} + ^{{j3}\; {kd}\; \alpha}} \right\}}}$

where α is sin θ_(s)−sin θ_(p). As can be easily seen, this is a1-2-3-4-3-2-1 weighting scheme on an array with access to more finelyspaced elements. In terms of the foregoing discussion, two collocatedarrays with elements on different phase centers are used. A 1-3-3-1weighting for the elements on integer phase centers is added to a 2-4-2weighting for the elements on half integer phase centers. Clearly,larger elements with centers spaced at larger D can be similarly createdwith more factors.

It should also be noted that wider nulls (i.e. more zeros) at thegrating lobes can be simply accommodated. Instead of a 1-2-1 digitalstacking technique that leads to a pair of zeros, one can derivecoefficients that correspond to four zeros as follows

$\mspace{79mu} {\cos^{4}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}$$\mspace{79mu} {{\cos^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}{\cos^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}$$\mspace{79mu} {\frac{1 + {\cos \left( {{kd}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}{2}*\frac{1 + {\cos \left( {{kd}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}{2}}$${\frac{1}{4}\left\lbrack {1 + \frac{^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + ^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}{2}} \right\rbrack}{\quad{\left\lbrack {1 + \frac{^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + ^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}{2}} \right\rbrack \mspace{79mu} \frac{^{{- {j2}}\; {kdsin}\; \alpha}1}{16}\left\{ {1 + {4^{j\; {kd}\; \alpha}} + {6^{{j2}\; {dk}\; \alpha}} + {4^{{j3}\; {kd}\; \alpha}} + ^{{j4}\; {kd}\; \alpha}} \right\}}}$

where α is sin θ_(s)−sin θ_(p). Clearly, more zeros could be createdwith the same technique.

An alternative way to eliminate the even grating lobes is to usenegative coefficients arising from the nulls imposed by the sinefunction. That is, a pair of zeros produced by a cosine function aspreviously shown for the odd grating lobes and a pair of zeros producedby a sine function shown below. Thus, it is desired to have

${\cos^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}{\sin^{2}\left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}$

As shown before, the zeros of the first cosine factor occur at

${{\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {{\pm m}\frac{\pi}{2}}};{m\mspace{14mu} {odd}}$${{2\frac{d}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {odd}}$

However, the zeros of the second sine factor occur at

${{\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {{\pm m}\frac{\pi}{2}}};{m\mspace{14mu} {even}}$${{2\frac{d}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm m}};{m\mspace{14mu} {even}}$

Comparing to the grating lobe equation

${\frac{d}{\lambda}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} = {\pm n}$

shows us that when D is large compared to λ/2, multiple grating lobesare created which are mitigated by elements that are half that size, theodd numbered ones by the cosine squared factor and the even numberedones by the sine squared factor.

Continuing on with the coefficient generation,

$\mspace{79mu} {\frac{1 + {\cos \left( {{kd}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}}{2}*\frac{1 - {\cos \left( {{kd}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right.}}{2}}$${\frac{1}{4}\left\lbrack {1 + \frac{^{j({{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + ^{- {j({{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}}{2}} \right\rbrack}{\quad\left\lbrack {1 + \frac{^{j({{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} - ^{- {j({{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}}{2}} \right\rbrack}$

Simplifying with the notation α=sin θ_(s)−sin θ_(p), and multiplying outthe factors into terms yields

$\frac{1}{16}\left\{ {4 + {2^{j\; {kd}\; \alpha}} - {2^{{- j}\; {kd}\; \alpha}} + {2^{{j2}\; {kd}\; \alpha}} - 1 + {2^{{- j}\; {kd}\; \alpha}} + 1 - ^{{- {j2}}\; {kd}\; \alpha}} \right\}$$\frac{^{{- {j2}}\; {kdsin}\; \alpha}}{16}\left\{ {{- 1} + {4^{{{j2}{kd}}\; \alpha}} + {4^{{j3}\; {kd}\; \alpha}} + ^{{j4}\; {kd}\; \alpha}} \right\}$

As can be easily seen, this is a {−1, 0, 4, 4, 1} weighting scheme on anarray with access to elements spaced half as far apart. Clearly, thisallows use of element sizes of a much larger pitch.

Instead of two pairs of zeros, one zero from the cosine and one from thesine factor can be used. Thus, it is desired to have

${\cos \left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}{\sin \left( {\frac{kd}{2}\left( {{\sin \; \theta_{s}} - {\sin \; \theta_{p}}} \right)} \right)}$

Continuing on with the coefficient generation,

$\left\lbrack \frac{^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} + ^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}{2} \right\rbrack\left\lbrack \frac{^{j\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}} - ^{{- j}\; {{kd}{({{\sin \; \theta_{s}} - {\sin \; \theta_{p}}})}}}}{2i} \right\rbrack$

Simplifying with the notation α=sin θ_(s)−sin θ_(p), and multiplying outthe factors into terms yields

$\frac{1}{4j}\left\{ {^{j\; 2{kd}\; \alpha} - 1 + j - ^{{- 2}j\; {kd}\; \alpha}} \right\}$$\frac{^{{- {j2}}\; {kd}\; \alpha}}{4j}\left\{ {{- 1} - {\left( {1 - j} \right)^{{j2}\; {kd}\; \alpha}} + ^{j\; 4\; {kd}\; \alpha}} \right\}$

As can be easily seen, this is a {−1, 0, j−1, 0, 1} weighting scheme onan array with access to the naturally spaced elements. Since every otherelement weight is zero, then this can be performed as a complexinterpolation at the larger element spacing, saving the need forgenerating delays. Clearly, grating lobes created by larger elementswith centers spaced further apart can be mitigated albeit with morenarrow nulls at the grating lobes.

An example of grating lobes without the digital stacking (“DS”)summation is shown in FIG. 8. In this case, 96 MHz resolution in thebeamforming was maintained for a Hanning window. The super element (SE)size in this case was 16. The grating lobes are quite effectivelymitigated by employing the DS approach at each stage removing the manygrating lobes arising from the various stages as seen in FIG. 9.

Comparing to the conventional beamforming method in FIG. 10, we find thedifferences are negligible.

Although the derivation above intimates a far field acoustic source,this effect also holds true for practical near field acoustic sources.The reason for this is that the DS solution makes use of the same effect(element spacing) as that which causes the grating lobes to begin with.That is, grating lobes caused by excessive spacing between delayedelement centers can be mitigated by using elements having centers athalf the distance. Although grating lobes are perfectly formed incontext of plane waves from the far field, the same effect, though notas perfect, occurs with near field waves which are not generally planar.But even in this case, to the degree they are formed, they can also bemitigated.

Aperture Reclamation (AR) and Aggregate weighting imposed by DS.

The effect of the 1-2-1 DS operation from stage to stage is to impose atriangular weighting function on the aperture. Consider the weightingsafter the first stage of delays and the first GLC summation.

se₀⁽²⁾ = e₀ + 2e₁ + e₂ se₁⁽²⁾ = e₂ + 2e₃ + e₄ se₂⁽²⁾ = e₄ + 2e₅ + e₆se₃⁽²⁾ = e₆ + 2e₇ + e₈ … se₆₂⁽²⁾ = e₁₂₄ + 2e₁₂₅ + e₁₂₆

Note the superscript (2) indicates it is a super-element of size 2. Thesubscripts indicate the relative order of the element or super-element.So in the above equation, the 1-2-1 weighting is applied to the actualelements to create the super-elements of the next stage reducing theelement count (e.g. from 127 elements to 63). Note that in thesesummations of the second stage super-elements there is a triangularweighting.

Now looking at the next stage of DS summation, we can write thefollowing in terms of the original elements.

$\begin{matrix}{\mspace{79mu} {{se}_{0}^{(4)} = {{se}_{0}^{(2)} + {2{se}_{1}^{(2)}} + {se}_{2}^{(2)}}}} \\{= {\left( {e_{0} + {2e_{1}} + e_{2}} \right) + {2\left( {e_{2} + {2e_{3}} + e_{4}} \right)} + \left( {e_{4} + {2e_{5}} + e_{6}} \right)}} \\{= {e_{0} + {2e_{1}} + {3e_{2}} + {4e_{3}} + {3e_{4}} + {2e_{5}} + e_{6}}}\end{matrix}$ $\mspace{79mu} \begin{matrix}{{se}_{1}^{(4)} = {{se}_{2}^{(2)} + {2{se}_{3}^{(2)}} + {se}_{4}^{(2)}}} \\{= {\left( {e_{4} + {2e_{5}} + e_{6}} \right) + {2\left( {e_{6} + {2e_{7}} + e_{8}} \right)} + \left( {e_{8} + {2e_{9}} + e_{10}} \right)}} \\{= {e_{4} + {2e_{5}} + {3e_{6}} + {4e_{7}} + {3e_{8}} + {2e_{9}} + e_{10}}}\end{matrix}$ $\begin{matrix}{\mspace{79mu} {{se}_{2}^{(4)} = {{se}_{4}^{(2)} + {2{se}_{5}^{(2)}} + {se}_{6}^{(2)}}}} \\{= {\left( {e_{8} + {2e_{9}} + e_{10}} \right) + {2\left( {e_{10} + {2e_{11}} + e_{12}} \right)} + \left( {e_{12} + {2e_{13}} + e_{14}} \right)}} \\{= {e_{8} + {2e_{9}} + {3e_{10}} + {4e_{11}} + {3e_{12}} + {2e_{13}} + e_{14}}}\end{matrix}$ $\begin{matrix}{{se}_{30}^{(4)} = {{se}_{60}^{(2)} + {2{se}_{61}^{(2)}} + {se}_{62}^{(2)}}} \\{= {\left( {e_{120} + {2e_{121}} + e_{122}} \right) + {2\left( {e_{122} + {2e_{123}} + e_{124}} \right)} + \left( {e_{124} + {2e_{125}} + e_{126}} \right)}} \\{= {e_{120} + {2e_{121}} + {3e_{122}} + {4e_{123}} + {3e_{124}} + {2e_{125}} + e_{126}}}\end{matrix}$

Note the triangular weighting in each of the above super-elements ofsize 4. This continues at each stage so that there are fewersuper-elements expressed as triangular weighted sums of more originalelements. This can be seen in FIG. 11 for the super-element of size 2.Note that the 1-2-1 summation creating a super-element is shown by thestacked arrangement of alternating shaded tiles. Looking up and down acolumn (identifying an original element) and adding up the number oftimes the same shade is used indicates the weighting for the particularoriginal element. This results in 1-2-1 weighting for the elementscontributing to the alternately shaded tiles. Note also that the arrowsindicate the center of the super-element and that there are about halfof them as the number of original elements.

Similarly, the next stage is depicted in the FIG. 12 wherein there areabout half as many arrows versus what is shown in FIG. 11, indicatingabout half as many super-elements that are twice as large. Thealternating shaded tiles indicate the elements summed to make the size 4super-elements. If we sum the number of occurrences of the same shade ina given column, we find the 1-2-3-4-3-2-1 weighting of the originalelements contributing to the super-elements.

Continuing on to the size 8 super-element stage we find a largertriangle function as shown in FIG. 13.

And finally, moving on to the size 16 super-elements we have a finalbeam sum that is created from these three super-elements as shown inFIG. 14. Here there will be a triangular weighting with the end elementsbeing weighted less than the center ones, that is, the aperture isapodized.

Effect on Aperture Size

As is typical with aperture apodization, the effect of this apertureweighting function is to increase the beam width and lower side lobelevels. Although the slightly lower side lobe levels are desirable, theloss of main beam resolution is not generally a desired result.

Figure of Reclamation Parallelograms

In FIG. 14, there are white areas indicating a lack of weighting to endelements relative to the center elements. These are left over from thevarious DS operations. These can be reclaimed by creating partial superelements as shown in FIG. 15 in the form of shaded parallelograms thatcan be delayed and added to the various beams. In this way, a betterresolution is created.

Similarity of Aperture Reclamation to Main Line Progressive Beam Forming

This aperture reclamation process is performed in the same staged way asthe mainline progressive beamforming process but with only data streamsfrom the end elements of each stage. FIG. 16 illustrates how thecontributions from the data streams from the end elements of each stageare reclaimed. Before the first DS operation in the mainline progressivebeam forming process, the data streams from the two end elements E₀ andE₁₂₆ of the center beam are buffered at 400. The data from these steamsare delayed to the center beamline. Next, the three streams focused onthe center beamline are buffered at blocks 402, 404 and 406. In blocks402 and 406, the data is re-delayed to focus the data on the outerbeamlines. The data at the center block 404 doesn't need to bere-delayed because it is already focused on a point along the centerbeamline.

At blocks 408, 410 and 412 the focused stream data is combined with datafrom the corresponding stage in the mainline process. That is, the datastreams at blocks 408, 410 and 412 are combined with the focused datastreams from end E0 and E62 from block 320 shown in FIG. 3. Thecombination can be accomplished by a simple summing of the correspondingelements.

In the next stage of the aperture reclamation process, the data issupplied to the buffers 414, 416, 418, 420 and 424 where the data areeither re-delayed to focus the data on a point on a new beamline or justbuffered if the data are already focused. The data for each beamline isthen combined with the corresponding mainline data that are focused. Forexample, block 426 combines the aperture reclamation data with the datastreams E₀ and E₃₀ produced by block 360 shown in FIG. 3. The aperturereclamation data at block 432 is combined with the data streams E₀ andE₃₀ that are focused on an interior beamline produced by correspondingblock 366 as shown in FIG. 3.

Processing continues in this manner by adding the streams from the endelements of each stage in the mainline beamforming process to the datastreams at each stage in the beam reclamation process. In oneembodiment, when the data streams for all 33 beamlines are created inthe beam reclamation process, the results are added back to the finalresult of the mainline progressive beamforming process as shown in FIG.17 to produce the output beamlines. In one embodiment, the values fromthe mainline beamline process are simply added with the values from theaperture reclamation process. For example, the value represented bymainline beam ML0 is added to the values in aperture reclamation lineAR0. At any stage in both the mainline and aperture reclamation process,the value for the beamline is computed by adding up the element values.In stage 4 of the mainline process shown in FIG. 3, the progressivebeamformer calculates 9 beams with 7 elements each. The value for anybeamline can be computed by adding together the values on each of the 7elements. If the aperture reclamation is to be added back in at thisstage, then the values of the 7 elements would be added to the 2elements computed in the corresponding aperture reclamation stage. Inthis way, all the weighting of the end elements can be reclaimed. Thisreclamation process consumes a fraction of the processing that the mainbeam requires.

Data Streaming

In contrast to many beamforming schemes wherein a central memory is usedat high bandwidth in the beamforming process, this approach needs onlysmall amounts of distributed local memory (such as FIFOs or othersuitable memories or electronic circuits) in sufficient depth toaccommodate the delays required to receive the first sample to be usedin a line. This, however, is not a restriction or limitation of thisapproach since element data can come either from the ADC devices orpreviously stored data in memory. In either case, memory bandwidth iskept to a minimum.

Delay Tables

Every delay block needs to be given the information on how to delay theincoming element to the proper locus of points (beamlines). Thisinformation is often stored as encoded tables. As beam densityincreases, the number of tables required also increases in proportion inconventional systems. However, this is not so with embodiments of thedisclosed progressive beamformer. With the progressive beamformer,individual tables are only needed with widely varying delay curves. Forexample, in stage 2 and 3 of the progressive beamformer, only two tablesper stage are needed with differing delay curves. However, in laterstages that fill in more beamlines per stage, greater numbers of tablesare used but the delay curves are nearly the same. As the bulk re-delayprocess is always relative to close neighboring beamlines, beamlinedelays all begin to converge to the same delay curve after a few stages.This is a tremendous advantage as the memory that stores delayinformation does not need to grow to a large size even when the linedensity becomes very fine.

In the forgoing discussion, a beamforming process has been describedthat can reduce by orders of magnitude the processing requirements formassive multi-line beamforming with little degradation to the imageperformance. This process makes progressive use of the beam formationprocess to make from one full set of elements delayed to a single line alarge number of other lines in multiple stages—wherein at each stage thenumber of super elements is halved through DS and the number ofbeamlines is doubled through a bulk re-delay (BRD) process. The DS wasrequired to suppress grating lobes at each stage. The DS produced atriangular apodization that reduced resolution which was easilycorrected by the aperture reclamation (AR) process.

Exemplary Additional Applications

Computed Volume Sonography (CVS): This is an efficient way to implementCVS where beams are computed at points in space that correspond topixels on a screen.

Scan Conversion: One additional application of this technology is thatof scan conversion. For beam data from curved or phased arrays followinga sampling grid based upon distance and angle, a fan of very closelyspaced beams can be made. When beam spacing becomes sufficiently dense,one only needs to select the nearest beam sample to the desired pixellocation.

For beam data acquisition that follows a Cartesian grid as in lineararrays, beam data may be computed to pixel locations directly orcorresponding to a decimation of those pixel locations. That is, thebeams are columns that may be either integer related to the pixelspacing or are fine enough density for a nearest neighbor approach.Thus, scan conversion can be accomplished fairly simply.

Analog Stacking (AS)

There is nothing in the method that mandates a digital system. Thusdigital stacking performed in a digital system could be replaced inwhole or in part by a similar procedure in the analog domain. This isparticularly important in high element count arrays such as 2D arrayswhere some beamforming processes may be done in the analog domain.

2D & 1.X D Arrays: Arrays with significantly more elements such as1.25D, 1.5D, 1.75D, or 2D arrays are particularly suited to thisprocessing as the beam locations form a two dimensional grid allowingfor a large number of beams to be generated in a small solid angle (asopposed to a simple lateral angle) with delays that are close to eachother. In a full 2D array, the DS operation may be performed as aseparable process of azimuth and elevation applications of the 1-2-1weighting. In this way, the element count reduces by a factor of four ateach stage, rapidly bringing channel counts down from 16384 (128×128array) to 512 or 64 channels.

Large Elements without Grating Lobes: Moreover, the DS does not have tobe done digitally; it can be done in analog domains especially withinthe scan head. Furthermore, there is no requirement that each DS musthave a delay operator preceding it so that more than one GLC stage canbe accomplished in either digital or analog domains prior to the delaystages so long as the super element directivity is consistent with thedesired steered look directions.

Re-Delaying from Lines Other than the Nearest Neighbor.

Given sufficient super element directivity, the nearest neighbor beamsare not the only ones that could be used. Combinations of beams furtheraway could also be used so long as the super element pattern supportsit.

Apodization Alternatives

If an apodization function is desired, it can be applied at the firststage (before the DS summation) to control the main lobe and side lobesof all the resulting beams.

Alternatively apodization can be applied in later stages as welldepending on the efficacy desired.

Synthetic Transmit Beamforming (STB)

Another extension to the PBF/DS approach is to incorporate synthetictransmit beamforming where multiple pings of one or more elements aremade separately and the transmit beam formation occurs simultaneouslywith the receive beam formation. This is not hard to understand as thesynthetic transmit contributors can be viewed as an additional factor onthe element count.

Aberration Correction

Since beamforming delays and re-delays are based on the speed of soundin the same way as traditional beamforming schemes, aberrationcorrection can applied in much the same way to this process in thecomputation of the delays just as it is done in traditional beamformingschemes.

Fast Color or Elastography

Fast Color or Elastography: Progressive Beam Forming can also be usedwith plane wave transmit and element acquisition systems using massiveparallel processors. Such approaches are used to compute very high framerate color or elastography images. The massive parallel beamforming ofPBD/DS supports these imaging modalities.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus.

A computer storage medium can be, or can be included in, acomputer-readable storage device, a computer-readable storage substrate,a random or serial access memory array or device, or a combination ofone or more of them. Moreover, while a computer storage medium is not apropagated signal, a computer storage medium can be a source ordestination of computer program instructions encoded in anartificially-generated propagated signal. The computer storage mediumalso can be, or can be included in, one or more separate physicalcomponents or media (e.g., multiple CDs, disks, or other storagedevices). The operations described in this specification can beimplemented as operations performed by a data processing apparatus ondata stored on one or more computer-readable storage devices or receivedfrom other sources.

The term “processor electronics” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus also can include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored on a non-transitory computer readable media in aportion of a file that holds other programs or data (e.g., one or morescripts stored in a markup language document), in a single filededicated to the program in question, or in multiple coordinated files(e.g., files that store one or more modules, sub-programs, or portionsof code). A computer program can be deployed to be executed on onecomputer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationnetwork.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device. Non-transitory computer readable mediadevices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., an LCD (liquid crystal display), LED(light emitting diode), or OLED (organic light emitting diode) monitor,for displaying information to the user and a keyboard and a pointingdevice, e.g., a mouse or a trackball, by which the user can provideinput to the computer. In some implementations, a touch screen can beused to display information and to receive input from a user. Otherkinds of devices can be used to provide for interaction with a user aswell; for example, feedback provided to the user can be any form ofsensory feedback, e.g., visual feedback, auditory feedback, or tactilefeedback; and input from the user can be received in any form, includingacoustic, speech, or tactile input. In addition, a computer can interactwith a user by sending documents to and receiving documents from adevice that is used by the user; for example, by sending web pages to aweb browser on a user's client device in response to requests receivedfrom the web browser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include any number of clients and servers. Aclient and server are generally remote from each other and typicallyinteract through a communication network. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

From the foregoing, it will be appreciated that specific embodiments ofthe invention have been described herein for purposes of illustration,but that various modifications may be made without deviating from thespirit and scope of the invention. For example, the data streams couldbe weighted with a non-linear or other function to reduce the gratinglobes. Accordingly, the invention is not to limited except as by theappended claims and equivalents thereof.

1. An imaging system, comprising: memory for buffering a number of datastreams of signals produced by transducer elements; and a number ofstages, each including processor electronics operable to delay andcombine at least a portion of data in the buffered data streams to aligndata to a point on a beamline within a field of view, wherein theprocessor electronics for stages after a first stage are operable tobuffer and re-delay at least a portion of the data streams from aprevious stage to align the data to a point on a new beamline, reducethe number of data streams that are aligned to a point on a beamline ina subsequent stage and increase an effective size of the transducerelements.
 2. The imaging system of claim 1, wherein the number of datastreams is reduced in each stage by combining data streams using aweighted sum of neighboring data streams.
 3. The imaging system of claim1, wherein the number of data streams is reduced by combining datastreams with a non-linear combination of beams.
 4. The imaging system ofclaim 3, wherein the non-linear combination is selected from one or moreof a maximum, a minimum and a median.
 5. The imaging system of claim 2,wherein alternating data streams are weighted with a 1-2-1 weighting ofadjacent data streams.
 6. (canceled)
 7. The imaging system of claim 2,wherein the combining is performed in the analog domain.
 8. The imagingsystem of claim 2, wherein the combining is performed in the digitaldomain.
 9. The imaging system of claim 2, wherein the reduction of thenumber of data streams for a subsequent stage results in fewer streamsthan every other stream.
 10. The imaging system of claim 1, wherein eachstage calculates data points for an increasing number of beamlines. 11.The imaging system of claim 1, wherein each stage calculates data pointsfor increasingly larger element spacings.
 12. The imaging system ofclaim 1, wherein each stage uses one or more delay tables to align thedata streams on a beamline, wherein at least some of the delay tablesare reused in later stages of the progressive beamformer.
 13. Theimaging system of claim 1, wherein the signals in the data streams areacoustic signals.
 14. The imaging system of claim 1, wherein the signalsin the data stream are electromagnetic signals.
 15. A progressivebeamforming system, including: a series of stages including a firststage and a number of subsequent stages, wherein the first stageincludes processor electronics that are configured to receive a numberof data streams from transducer elements that represent signals from afield of view, wherein the processor electronics are configured to delaythe data streams to align the data streams to a point of interest on afirst beamline and to reduce the number of data streams; whereinsubsequent stages include processor electronics that are configured toreceive data streams from a previous stage and to re-delay the receiveddata streams to align the data streams to a point of interest on a newbeamline and to reduce the number of data streams that are aligned to apoint on a beamline in a subsequent stage.
 16. The progressivebeamforming system of claim 15, wherein each stage reduces the number ofdata streams by weighting selected data streams with a weight that isgreater amount than a weight applied to adjacent data streams andsumming the data stream with its adjacent data streams.
 17. Theprogressive beamforming system of claim 15, wherein selected data streamare weighted with a weight that is twice the weight of its adjacent datastreams.
 18. The progressive beamforming system of claim 15, wherein thebeamlines produced are part of a mainline beamforming process and thesystem further includes a number of beam reclamation stages that receivedata streams from a previous stage, buffer and re-delay the data streamsto a new beam line and to add streams from end elements of acorresponding stage in the mainline beamforming process in order toproduce a reclaimed beamline that is added back to a beamline producedin the mainline beamforming process in order to produce an outputbeamline.
 19. A beamformer comprising: a mainline progressive beamformerthat is configured to delay digital signals from a transducer to focusthe signals on a point of interest on a number of beamlines, wherein themainline beamformer operates to re-delay stored signals that are focusedon one beamline in order to focus the digital signals on a new beamline;and an aperture reclamation beamformer that is configured to delaysignals from end elements of a transducer and combine them with delayedsignals from the mainline progressive beamformer in order to producedata for a point on a beamline.
 20. The beamformer of claim 19, whereinthe mainline progressive beamformer is arranged in a number of stages,wherein each stage adds data for new beamlines.
 21. The beamformer ofclaim 20, wherein each stage after a 2nd stage is configured to add datafor beamlines that are interleaved with data for previously computedbeamlines. 22-24. (canceled)